In cancer, linking epigenetic alterations to drivers of transformation has been difficult, in part because DNA methylation analyses must capture epigenetic variability, which is central to tumour heterogeneity and tumour plasticity. Here, by conducting a comprehensive analysis, based on information theory, of differences in methylation stochasticity in samples from patients with paediatric acute lymphoblastic leukaemia (ALL), we show that ALL epigenomes are stochastic and marked by increased methylation entropy at specific regulatory regions and genes. By integrating DNA methylation and single-cell gene-expression data, we arrived at a relationship between methylation entropy and gene-expression variability, and found that epigenetic changes in ALL converge on a shared set of genes that overlap with genetic drivers involved in chromosomal translocations across the disease spectrum. Our findings suggest that an epigenetically driven gene-regulation network, with UHRF1 (ubiquitin-like with PHD and RING finger domains 1) as a central node, links genetic drivers and epigenetic mediators in ALL.
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DNA-methylation and RNA-seq data are available at the Gene Expression Omnibus repository under the accession number GSE116229.
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This work was supported by US National Institutes of Health grants R01 CA65438 and DP1 DK119129 to A.P.F., R01 HG006282 to H.J., US National Science Foundation grant CCF-1656201 to J.G., St. Baldrick’s Foundation fellowship and funding from Unravel Pediatric Cancer to M.A.K. M.A.K. is a Damon Runyon–Sohn Pediatric Cancer Fellow supported by the Damon Runyon Cancer Research Foundation (DRSG-15P-16). The funders had no role in study design, data collection and analysis, decision to publish or preparation of the manuscript.
The authors declare no competing interests.
Peer review information Nature Biomedical Engineering thanks the anonymous reviewers for their contribution to the peer review of this work.
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Koldobskiy, M.A., Jenkinson, G., Abante, J. et al. Converging genetic and epigenetic drivers of paediatric acute lymphoblastic leukaemia identified by an information-theoretic analysis. Nat Biomed Eng 5, 360–376 (2021). https://doi.org/10.1038/s41551-021-00703-2
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